Improving prophylaxis for pollen allergies: Predicting the time course of the pollen load of the atmosphere of major allergenic plants in France and Spain

Chuine, Isabelle; Belmonte, Jordina

doi:10.1080/00173130410019163

Cited by 36 publications

(22 citation statements)

References 39 publications

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“…In low but frost-free temperatures, only a few anthers open at one time. Moreover, a platykurtic pollen curve can be due to the existence of environmental and genetic variation for fl owering time within populations and species, as has been documented for numerous species (Primack 1985 ;Wielgolaski 1999 ;Chuine and Belmonte 2004 ) .…”

Section: Duration Of the Pollen Season And The Shape Of The Pollen Curvementioning

confidence: 97%

The Onset, Course and Intensity of the Pollen Season

et al. 2012

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The onset, duration and intensity of the period when pollen is present in the air varies from year to year. Amongst other things, there is an effect upon the quality of life of allergy sufferers. The production and emission of pollens are governed by interacting environmental factors. Any change in these factors may affect the phenology and intensity of the season. Readiness to fl ower in a plant, and the amount of pollen produced, is the result of conditions during an often long period foregoing fl owering. When a plant is ready to fl ower, temporary ambient circumstances e.g., irradiation and humidity, determine the timing of the actual

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Section: Duration Of the Pollen Season And The Shape Of The Pollen Curvementioning

confidence: 97%

The Onset, Course and Intensity of the Pollen Season

et al. 2012

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“…Atmospheric concentrations of grass pollen are commonly forecasted and published in order to facilitate self-care among grass pollen allergic subjects. The forecasting of grass pollen concentrations is generally done with statistical models (Chuine and Belmonte, 2004;Garcìa-Mozo et al, 2009;Laaidi, 2001;Emberlin, 2005, 2006). Statistical or empirical forecast models are, by their nature, limited to the area where they are produced .…”

Section: Introductionmentioning

confidence: 99%

Identifying urban sources as cause of elevated grass pollen concentrations using GIS and remote sensing

et al. 2013

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We examine here the hypothesis that during flowering, the grass pollen concentrations at a specific site reflect the distribution of grass pollen sources within a few kilometres of this site. We perform this analysis on data from a measurement campaign in the city of Aarhus (Denmark) using three pollen traps and by comparing these observations with a novel inventory of grass pollen sources. The source inventory is based on a new methodology developed for urban-scale grass pollen sources. The new methodology is believed to be generally applicable for the European area, as it relies on commonly available remote sensing data combined with management information for local grass areas. The inventory has identified a number of grass pollen source areas present within the city domain. The comparison of the measured pollen concentrations with the inventory shows that the atmospheric concentrations of grass pollen in the urban zone reflect the source areas identified in the inventory, and that the pollen sources that are found to affect the pollen levels are located near or within the city domain. The results also show that during days with peak levels of pollen concentrations there is no correlation between the three urban traps and an operational trap located just 60 km away. This finding suggests that during intense flowering, the grass pollen concentration mirrors the local source distribution and is thus a local-scale phenomenon. Model simulations aimed at assessing population exposure to pollen levels are therefore recommended to take into account both local sources and local atmospheric transport, and not to rely only on describing regional to long-range transport of pollen. The derived pollen source inventory can be entered into local-scale atmospheric transport models in combination with other components that simulate pollen release in order to calculate urban-scale variations in the grass pollen load. The gridded inventory with a resolution of 14 m is therefore made available as supplementary material to this paper, and the verifying grass pollen observations are additionally available in tabular form

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“…It's delay can be as short as 1 h (Crouzy et al, 2016;Oteros et al, 2015b). These data have good potential to be used for next-day predictions for the vicinity of the monitor.…”

Section: Fusing the Model Predictions And Observationsmentioning

confidence: 99%

“…Aguilera et al (2014). A switch to different types of phenological models with genetic differentiation of the populations following Chuine and Belmonte (2004) is another promising option.…”

Section: Main Challenges For the Future Studiesmentioning

confidence: 99%

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Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

et al. 2017

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Abstract. The paper presents the first modelling experiment of the European-scale olive pollen dispersion, analyses the quality of the predictions, and outlines the research needs. A 6-model strong ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run throughout the olive season of 2014, computing the olive pollen distribution. The simulations have been compared with observations in eight countries, which are members of the European Aeroallergen Network (EAN). Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimised combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season was reported to start too early by 8 days, but for some models the error mounted to almost 2 weeks. For the end of the season, the disagreement between the models and the observations varied from a nearly perfect match up to 2 weeks too late. A series of sensitivity studies carried out to understand the origin of the disagreements revealed the crucial role of ambient temperature and consistency of its representation by the meteorological models and heat-sum-based phenological model. In particular, a simple correction to the heat-sum threshold eliminated the shift of the start of the season but its validity in other years remains to be checked. The short-term features of the concentration time series were reproduced better, suggesting that the precipitation events and cold/warm spells, as well as the large-scale transport, were represented rather well. Ensemble averaging led to more robust results. The best skill scores were obtained with data fusion, which used the previous days' observations to identify the optimal weighting coefficients of the individual model forecasts. Such combinations were tested for the forecasting period up to 4 days and shown to remain nearly optimal throughout the whole period.

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Improving prophylaxis for pollen allergies: Predicting the time course of the pollen load of the atmosphere of major allergenic plants in France and Spain

Cited by 36 publications

References 39 publications

The Onset, Course and Intensity of the Pollen Season

The Onset, Course and Intensity of the Pollen Season

Identifying urban sources as cause of elevated grass pollen concentrations using GIS and remote sensing

Multi-model ensemble simulations of olive pollen distribution in Europe in 2014: current status and outlook

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